生物多样性 ›› 2011, Vol. 19 ›› Issue (2): 168-177.doi: 10.3724/SP.J.1003.2011.10107

所属专题: 中国的森林生物多样性监测

• 研究报告 • 上一篇    下一篇

亚热带常绿阔叶林群落物种多度分布格局对取样尺度的响应

程佳佳1, 2, 米湘成2, 马克平2, 张金屯1*   

  1. 1北京师范大学生命科学学院, 北京 100875
    2中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
  • 收稿日期:2010-04-28 修回日期:2010-07-15 出版日期:2011-03-21
  • 通讯作者: 张金屯 E-mail:zhangjt@bnu.edu.cn; zhangjintun@yahoo.com.cn

Responses of species–abundance distribution to varying sampling scales in a subtropical broad-leaved forest

Jiajia Cheng1, 2, Xiangcheng Mi2, Keping Ma2, Jintun Zhang1*   

  1. 1College of Life Sciences, Beijing Normal University, Beijing 100875

    2State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
  • Received:2010-04-28 Revised:2010-07-15 Online:2011-03-21
  • Contact: Jintun Zhang E-mail:zhangjt@bnu.edu.cn; zhangjintun@yahoo.com.cn

为揭示物种多度格局随尺度的变化规律, 探讨多度格局形成的机理及生态学过程, 作者以古田山亚热带常绿阔叶林24 ha固定监测样地为背景, 采用断棍模型(broken stick model)、对数正态模型(lognormal distribution model)、生态位优先占领模型(preemption model)、Zipf模型(Zipf model)、Zipf-Mandelbrot模型(Zipf-Mandelbrot model)及中性理论模型(neutral model), 对不同尺度下的物种多度分布格局进行拟合, 并采用AIC检验和卡方检验选择最优拟合模型。结果表明, 不同尺度上适合的物种–多度曲线模型不同; 在取样边长为10 m和20 m时, 除中性模型外的5个模型均不能被拒绝, 它们均适合小尺度下的格局, 这表明在小的尺度上生态位过程对物种–多度曲线的格局贡献较大; 在取样边长为40 m时, 最适合的模型为对数正态模型; 取样边长为60 m和80 m时, Zipf-Mandelbrot模型为最优拟合模型; 在取样边长为100 m时, 尽管Zipf-Mandelbrot模型有最小的AIC值, 但卡方检验拒绝了除中性模型外的5个模型; 中性理论模型除了边长为10 m和20 m尺度以外, 在其他尺度上均比前面5种模型的预测效果更好。因此在研究物种多度分布规律时必须注意空间尺度的影响。研究结果表明随着尺度的增加, 中性过程成为决定物种–多度曲线格局的主要生态过程。

We determined the best-fit model for, and explored the mechanisms shaping species–abundance distributions (SADs) by fitting five widely-used SAD distribution models at several scales. We used data collected in 2005 from a 24-ha dynamic plot in an evergreen broad-leaved forest in the Gutianshan National Nature Reserve. We estimated SAD at different sampling scales from the mean value of SADs taken from 100 randomly-selected subplots within the 600 m×400 m Gutianshan plot. We subsequently used the SADs to test the fit of different models, including the broken stick, lognormal distribution, niche preemption, Zipf, Zipf- Mandelbrot, and neutral models. We employed AIC and χ2 values to test goodness-of-fit for these models. All computations were conducted using the Vegan package in R 2.7.1. At smaller scales (10 m×10 m and 20 m×20 m), the broken stick, lognormal distribution, niche preemption, Zipf, and Zipf-Mandelbrot models all fit well to the observed species–abundance distribution. The Zipf-Mandelbrot was the best model at the 20 m×20 m scale. The Lognormal was the best-fit model at the 40 m×40 m scale, and the Zipf-Mandelbrot model was the only suitable one in explaining the observed SAD at scales of 60 m×60 m and 80 m×80 m. None of these models performed well at a scale of 100 m×100 m, but the neutral model was better at explaining patterns of SADs at larger scales (40 m×40 m to 100 m×100 m) than smaller scales and it is suitable in explaining patterns of SADs at all scales. Patterns in SAD were scale-dependent, suggesting that SADs at different scales are likely structured by different ecological processes.

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